Stochastic factors and string stability of traffic flow: Analytical investigation and numerical study based on car-following models
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影响因子：6.8
发表刊物：Transportation Research Part B: Methodological
摘要：The emergence dynamics of traffic instability has always attracted particular attention. For several decades, researchers have studied the stability of traffic flow using deterministic traffic models, with less emphasis on the presence of stochastic factors. However, recent empirical and theoretical findings have demonstrated that the stochastic factors tend to destabilize traffic flow and stimulate the concave growth pattern of traffic oscillations. In this paper, we derive a string stability condition of a general stochastic continuous car-following model by the mean of the generalized Lyapunov equation. We have found, indeed, that the presence of stochasticity destabilizes the traffic flow. The impact of stochasticity depends on both the sensitivity to the gap and the sensitivity to the velocity difference. Numerical simulations of three typical car-following models have been carried out to validate our theoretical analysis. Finally, we have calibrated and validated the stochastic car-following models against empirical data. It is found that the stochastic car-following models reproduce the observed traffic instability and capture the concave growth pattern of traffic oscillations. Our results further highlight theoretically and numerically that the stochastic factors have a significant impact on traffic dynamics.
第一作者：Marouane Bouadi, Bin Jia, Rui Jiang, Xingang Li, Zi-You Gao
论文类型：期刊论文
论文编号：96-122
卷号：165
是否译文：否
发表时间：2022-11-07
收录刊物：SCI、SSCI